The present technology relates to imaging systems and methods for decoding images, and more specifically, to imaging systems and methods for stitching and decoding images using data combined from multiple captured images.
Imaging systems use image acquisition devices that include camera sensors to deliver information on a viewed subject. The system then interprets this information according to a variety of algorithms to perform a programmed decision-making and/or identification function. For an image to be most-effectively acquired by a sensor in the visible, and near-visible light range, the subject is typically illuminated.
Symbology reading (also commonly termed “barcode” scanning) using an image sensor, entails the aiming of an image acquisition sensor (CMOS camera, CCD, etc.) at a location on an object that contains a symbol (a “barcode” for example), and acquiring an image of that symbol. The symbol contains a set of predetermined patterns that represent an ordered group of characters or shapes from which an attached data processor (for example a microcomputer) can derive useful information about the object (e.g. its serial number, type, model, price, etc.). Symbols/barcodes are available in a variety of shapes and sizes. Two of the most commonly employed symbol types used in marking and identifying objects are the so-called one-dimensional barcode, consisting of a line of vertical stripes of varying width and spacing, and the so-called two-dimensional barcode consisting of a two-dimensional array of dots or rectangles.
In many imaging applications, surface features, illumination, movement, vibration or a multitude of other variations can result in an image that, on its own, can be partially unreadable. For example, an imaging system can derive a plurality of images of a symbol on an object as the object is moving down a conveyor line. In this arrangement, relative movement between the imaging device and the object occurs. A machine vision application embedded in the processing circuitry of the imaging system derives a plurality of images of the symbol on the object. For any of the reasons above, one or more of the derived image can be partially unreadable.
While the exemplary machine vision detector may acquire multiple images of the object/feature of interest as it passes through the field of view, each image is used individually to perform a detection and/or triggering function.